Abstract

Actual evapotranspiration (ET) with high spatiotemporal resolution is very important for the research on agricultural water resource management and the water cycle processes, and it is helpful to realize precision agriculture and smart agriculture, and provides critical references for agricultural layout planning. Due to the impact of the clouds, weather environment, and the orbital period of optical satellite, there are difficulties in providing daily remote sensing data that are not contaminated by clouds for estimating daily ET with high spatial-temporal resolution. By improving the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM), this manuscript proposes the method to fuse high temporal and low spatial resolution Weather Research and Forecasting (WRF) model surface skin temperature (TSK) with the low temporal and high spatial resolution remote sensing surface temperature for obtaining high spatiotemporal resolution daily surface temperature to be used in the estimation of the high spatial resolution daily ET (ET_WRFHR). The distinction of this study from the previous literatures can be summarized as the novel application of the fusion of WRF-simulated TSK and remote sensing surface temperature, giving full play to the availability of model surface skin temperature data at any time and region, making up for the shortcomings of the remote sensing data, and combining the high spatial resolution of remote sensing data to obtain ET with high spatial (Landsat-like scale) and temporal (daily) resolution. The ET_WRFHR were cross-validated and quantitatively verified with MODIS ET products (MOD16) and observations (ET_Obs) from eddy covariance system. Results showed that ET_WRFHR not only better reflects the difference and dynamic evolution process of ET for different land types but also better identifies the details of various fine geographical objects. It also represented a high correlation with the ET_Obs by the R2 amount reaching 0.9186. Besides, the RMSE and BIAS between ET_WRFHR and the ET_Obs are obtained as 0.77 mm/d and −0.08 mm/d respectively. High R2, as well as the small RMSE and BIAS amounts, indicate that ET_WRFHR has achieved a very good performance.

Highlights

  • Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations

  • Lines and the samples keep the same and the bilinear interpolation method is selected for Equationto(1)reduce is used to normalize the fusion results inofthe fourth step a resampling the impact of geographic reference errors.obtained

  • To achieve daily ET with high spatialtemporal resolution, ET is estimated as the first step based on the Surface energy balance system (SEBS) model by using the surface temperature with high spatiotemporal resolution obtained by the fusion algorithm

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Summary

Description of theisStudy

Areain the middle of the Hexi Corridor in the arid and semi-arid regionsThe of northwest. Corridor in the arid 510 km long fromand north to south. 2 , which km long from north to south. It covers an area approximately is the second-largest inland river basin in China With 143,000 a total km length of is the second-largest inland river basin in China. Mountain in the south and moistens moistens the vast area of Ejina Banner in the north. Zhangye Oasis area (46 km × 46 km), the vast area of Ejina Banner in the north. Zhangye Oasis area (46 km × 46 km), shown in shown in the right panel of Figure 1, is the study area, which is located in the HRB midthe right panel of Figure 1, is the study area, which is located in the HRB midstream where stream where the the desert-oasis exists.The. Thepredominant predominant crops inregion this region are wheat desert-oasislandscape landscape exists. River (left)River andBasin the study area [43].(right) [43]

Ground Measurements
May–29
Satellite Data
Surface Skin Temperature
WRF Model Experiments
Three nested domains displayed on a Global
Process of obtaining temperature with high spatiotemporal
ET Estimation Scheme for High Spatiotemporal Surface Temperature
Evaluation Method
Evaluation of High Spatiotemporal Resolution Surface Temperature
Results show
Spatial of High
Dynamic
Discussion
Comparison with MOD16 in Identifying Fine Features
28 July–4
ET Spatial Distribution of Target Geography Objects
10. High-resolution
ET Dynamic Evolution of Target Geography Objects
ET Dynamic Evolution of Target Geography Objects thethe
Quantitative with
Quantitative Verification with Observations
Conclusions
Full Text
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